Abstract

Variations in the postures of pigs can contribute to significant amounts of error during
automatic weight estimation of pigs using image analysis techniques. This is especially the case
when the head of a pig is not maintained on the same straight line as the body of the animal. It
was estimated that an additional 2.4% error is associated with sub-optimal posture of animals
during weight estimation. To minimize weight estimation error as much as possible, the aim
of this study was to identify the most suitable image analysis technique that can automatically
select frames from video streams with optimum animal posture for accurate weight
estimation. Four different techniques, namely reference line, length ratio, angular width and
mid-line methods were investigated using images of pigs between 45 and 90 kg. All images
were taken from above the animals at a height of 1680 mm. In this study, images of animals
turning their heads more than 30 degrees from the body line either left or right were classified
as suboptimal. Similarly, images were also classified as suboptimal if the angular placement of
the pigs in the images were more than 30 degrees from the midline. Among the different
methods, both the length ratio and angular width method were found to be most likely to
identify images with suboptimal head position, while the midline method was the best at
identifying pigs with a suboptimal body position. Thus overall the length ratio method appears
to be the best to identify suboptimal images before further processing.